Prognostic utility of the 21-gene assay in hormone receptor-positive operable breast cancer compared with classical clinicopathologic features

High estrogen receptor expression in early breast cancer: chemotherapy needed to improve RFS?

One of the most controversial questions in early breast cancer treatment is the need of chemotherapy in patients with estrogen receptor positive disease. Therefore, we analyzed a group of patients with high estrogen receptor (ER) expression to scrutinize the role of chemotherapy in this situation. To gauge the effect of chemotherapy on recurrence free survival (RFS) three treatment modalities were compared: endocrine treatment only, chemoendocrine treatment, and chemotherapy. 3,971 breast cancer patients whose treatment modalities as well as ER level were known, were included in this retrospective analysis. Their level of ER expression was documented as immunoreactive score (IRS). A high ER group was defined as ER IRS ≥ 9; primary endpoint was RFS. RFS was associated with ER, with the best outcome for strong and the worst result for negative expression. Adjusted to Nottingham prognostic index (NPI), RFS did not differ between the treatment cohorts of endocrine treatment and chemoendocrine treatment (P = 0.828) in the high ER group. Patients with chemotherapy alone fared significantly worse (P = 0.003). Even in high risk patients (according to NPI) the chemoendocrine and the endocrine treatment only groups did not differ significantly (HR = 1.15; 95% CI (0.56-2.34), P = 0.709). Omission of endocrine treatment led to significantly worse outcome (P = 0.013). In conclusion, RFS was significantly longer in patients with high ER expression than with weak or no ER expression. In the high expression group, there was no significant difference in RFS between endocrine treatment only and chemoendocrine therapy-even in high risk patients, for whom chemoendocrine treatment is routinely indicated. It seems insufficient for high ER patients to only consider tumor size, nodal status, and grading in order to decide which patient will benefit from adding chemotherapy to endocrine treatment.

Gene expression profiling: changing face of breast cancer classification and management

Epithelial breast malignancies are a group of several disease entities that vary in their biology and response to specific therapies. Historically, classification of different molecular types of breast cancer was done through the use of conventional methods such as tumor morphology, grade, and immunophenotyping for estrogen, progesterone, and HER-2/neu receptor expression. Such techniques, although helpful, are not sufficient to accurately predict biologic behavior of breast cancers. Over the last several years, much progress has been made in more precise identification of molecular breast cancer subtypes. Such advances hold a great promise in improving estimation of prognosis and assigning most appropriate therapies. Thanks to use of cDNA microarrays expression technology and quantitative reverse transcriptase polymerase chain reaction (RT-PCR), tumors with specific gene expression patterns can now be identified. This process is presently reshaping perceptions of how breast cancer should be classified and treated. Categorization of breast cancers by gene expression is only beginning to make its way into the daily clinical practice and likely will complement, but not replace, the conventional methods of classification.

Gene expression profiling for guiding adjuvant chemotherapy decisions in women with early breast cancer: an evidence-based and economic analysis

In February 2010, the Medical Advisory Secretariat (MAS) began work on evidence-based reviews of published literature surrounding three pharmacogenomic tests. This project came about when Cancer Care Ontario (CCO) asked MAS to provide evidence-based analyses on the effectiveness and cost-effectiveness of three oncology pharmacogenomic tests currently in use in Ontario.Evidence-based analyses have been prepared for each of these technologies. These have been completed in conjunction with internal and external stakeholders, including a Provincial Expert Panel on Pharmacogenomics (PEPP). Within the PEPP, subgroup committees were developed for each disease area. For each technology, an economic analysis was also completed by the Toronto Health Economics and Technology Assessment Collaborative (THETA) and is summarized within the reports.THE FOLLOWING REPORTS CAN BE PUBLICLY ACCESSED AT THE MAS WEBSITE AT: www.health.gov.on.ca/mas or at www.health.gov.on.ca/english/providers/program/mas/mas_about.htmlGENE EXPRESSION PROFILING FOR GUIDING ADJUVANT CHEMOTHERAPY DECISIONS IN WOMEN WITH EARLY BREAST CANCER: An Evidence-Based and Economic AnalysisEpidermal Growth Factor Receptor Mutation (EGFR) Testing for Prediction of Response to EGFR-Targeting Tyrosine Kinase Inhibitor (TKI) Drugs in Patients with Advanced Non-Small-Cell Lung Cancer: An Evidence-Based and Ecopnomic AnalysisK-RAS testing in Treatment Decisions for Advanced Colorectal Cancer: an Evidence-Based and Economic Analysis

OBJECTIVE

To review and synthesize the available evidence regarding the laboratory performance, prognostic value, and predictive value of Oncotype-DX for the target population.

CLINICAL NEED

CONDITION AND TARGET POPULATION The target population of this review is women with newly diagnosed early stage (stage I-IIIa) invasive breast cancer that is estrogen-receptor (ER) positive and/or progesterone-receptor (PR) positive. Much of this review, however, is relevant for women with early stage (I and II) invasive breast cancer that is specifically ER positive, lymph node (LN) negative and human epidermal growth factor receptor 2 (HER-2/neu) negative. This refined population represents an estimated incident population of 3,315 new breast cancers in Ontario (according to 2007 data). Currently it is estimated that only 15% of these women will develop a distant metastasis at 10 years; however, a far great proportion currently receive adjuvant chemotherapy, suggesting that more women are being treated with chemotherapy than can benefit. There is therefore a need to develop better prognostic and predictive tools to improve the selection of women that may benefit from adjuvant chemotherapy. TECHNOLOGY OF CONCERN: The Oncotype-DX Breast Cancer Assay (Genomic Health, Redwood City, CA) quantifies gene expression for 21 genes in breast cancer tissue by performing reverse transcription polymerase chain reaction (RT-PCR) on formalin-fixed paraffin-embedded (FFPE) tumour blocks that are obtained during initial surgery (lumpectomy, mastectomy, or core biopsy) of women with early breast cancer that is newly diagnosed. The panel of 21 genes include genes associated with tumour proliferation and invasion, as well as other genes related to HER-2/neu expression, ER expression, and progesterone receptor (PR) expression.

RESEARCH QUESTIONS

What is the laboratory performance of Oncotype-DX?How reliable is Oncotype-DX (i.e., how repeatable and reproducible is Oncotype-DX)?How often does Oncotype-DX fail to give a useable result?What is the prognostic value of Oncotype-DX?Is Oncotype-DX recurrence score associated with the risk of distant recurrence or death due to any cause in women with early breast cancer receiving tamoxifen?What is the predictive value of Oncotype-DX?Does Oncoytpe-DX recurrence score predict significant benefit in terms of improvements in 10-year distant recurrence or death due to any cause for women receiving tamoxifen plus chemotherapy in comparison to women receiving tamoxifen alone?How does Oncotype-DX compare to other known predictors of risk such as Adjuvant! Online?How does Oncotype-DX impact patient quality of life and clinical/patient decision-making?

SEARCH STRATEGY

A literature search was performed on March 19(th), 2010 using OVID MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, the Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Cochrane Library, and the International Agency for Health Technology Assessment (INAHTA) for studies published from January 1(st), 2006 to March 19(th), 2010. A starting search date of January 1(st), 2006 was because a comprehensive systematic review of Oncotype-DX was identified in preliminary literature searching. This systematic review, by Marchionni et al. (2008), included literature up to January 1(st), 2007. All studies identified in the review by Marchionni et al. as well as those identified in updated literature searching were used to form the evidentiary base of this review. The quality of the overall body of evidence was identified as high, moderate, low or very low according to GRADE methodology.

INCLUSION CRITERIA

Any observational trial, controlled clinical trial, randomized controlled trial (RCT), meta-analysis or systematic review that reported on the laboratory performance, prognostic value and/or predictive value of Oncotype-DX testing, or other outcome relevant to the Key Questions, specific to the target population was included.

EXCLUSION CRITERIA

Studies that did not report original data or original data analysis,Studies published in a language other than English,Studies reported only in abstract or as poster presentations (such publications were not sought nor included in this review since the MAS does not generally consider evidence that is not subject to peer review nor does the MAS consider evidence that lacks detailed description of methodology).

OUTCOMES OF INTEREST

Outcomes of interest varied depending on the Key Question. For the Key Questions of prognostic and predictive value (Key Questions #2 and #3), the prospectively defined primary outcome was risk of 10-year distant recurrence. The prospectively defined secondary outcome was 10-year death due to any cause (i.e., overall survival). All additional outcomes such as risk of locoregional recurrence or disease-free survival (DFS) were not prospectively determined for this review but were reported as presented in included trials; these outcomes are referenced as tertiary outcomes in this review. Outcomes for other Key Questions (i.e., Key Questions #1, #4 and #5) were not prospectively defined due to the variability in endpoints relevant for these questions.

SUMMARY OF FINDINGS

A total of 26 studies were included. Of these 26 studies, only five studies were relevant to the primary questions of this review (Key Questions #2 and #3). The following conclusions were drawn from the entire body of evidence: There is a lack of external validation to support the reliability of Oncotype-DX; however, the current available evidence derived from internal industry validation studies suggests that Oncotype-DX is reliable (i.e., Oncotype-DX is repeatable and reproducible).Current available evidence suggests a moderate failure rate of Oncotype-DX testing; however, the failure rate observed across clinical trials included in this review is likely inflated; the current Ontario experience suggests an acceptably lower rate of test failure.In women with newly diagnosed early breast cancer (stage I-II) that is estrogen-receptor positive and/or progesterone-receptor positive and lymph-node negative:There is low quality evidence that Oncotype-DX has prognostic value in women who are being treated with adjuvant tamoxifen or anastrozole (the latter for postmenopausal women only),There is very low quality evidence that Oncotype-DX can predict which women will benefit from adjuvant CMF/MF chemotherapy in women being treated with adjuvant tamoxifen.In postmenopausal women with newly diagnosed early breast cancer that is estrogen-receptor positive and/or progesterone-receptor positive and lymph-node positive:There is low quality evidence that Oncotype-DX has limited prognostic value in women who are being treated with adjuvant tamoxifen or anastrozole,There is very low quality evidence that Oncotype-DX has limited predictive value for predicting which women will benefit from adjuvant CAF chemotherapy in women who are being treated with adjuvant tamoxifen.There are methodological and statistical limitations that affect both the generalizability of the current available evidence, as well as the magnitude and statistical strength of the observed effect sizes; in particular:Of the major predictive trials, Oncotype-DX scores were only produced for a small subset of women (<40% of the original randomized population) potentially disabling the effects of treatment randomization and opening the possibility of selection bias;Data is not specific to HER-2/neu-negative women;There were limitations with multivariate statistical analyses.Additional trials of observational design may provide further validation of the prognostic and predictive value of Oncotype-DX; however, it is unlikely that prospective or randomized data will become available in the near future due to ethical, time and resource considerations.There is currently insufficient evidence investigating how Oncoytpe-DX compares to other known prognostic estimators of risk, such as Adjuvant! Online, and there is insufficient evidence investigating how Oncotype-DX would impact clinician/patient decision-making in a setting generalizable to Ontario.

Use of standard markers and incorporation of molecular markers into breast cancer therapy: Consensus recommendations from an International Expert Panel

Breast cancer is a heterogeneous disease of different subtypes on the molecular, histopathological, and clinical level. Genomic profiling techniques have led to several prognostic and predictive gene signatures of breast cancer that may further refine outcome prediction, especially in clinically equivocal situations. In particular, the predictive value of today's most important therapeutic targets, ER and HER2, are strongly influenced by the proliferative status of the tumor. Genomic assays are generally performed in a centralized manner, whereas routine pathological evaluation is mostly done on a decentralized basis, making the comparison of these methods difficult. Thus, there remains considerable uncertainty about the use of the new molecular markers in routine clinical decision making and their role in patient selection or stratification for future clinical trials. To address this concern, a group of representatives from breast cancer research groups in the areas of breast pathology, genomic profiling, and clinical trials critically reviewed all available data. Consensus recommendations are made on the practical use of molecular markers in breast cancer management and their incorporation into future clinical trials.

Predicting prognosis of breast cancer with gene signatures: are we lost in a sea of data?

A large number of prognostic and predictive signatures have been proposed for breast cancer and a few of these are now available in the clinic as new molecular diagnostic tests. However, several other signatures have not fared well in validation studies. Some investigators continue to be puzzled by the diversity of signatures that are being developed for the same purpose but that share few or no common genes. The history of empirical development of prognostic gene signatures and the unique association between molecular subsets and clinical phenotypes of breast cancer explain many of these apparent contradictions in the literature. Three features of breast cancer gene expression contribute to this: the large number of individually prognostic genes (differentially expressed between good and bad prognosis cases); the unstable rankings of differentially expressed genes between datasets; and the highly correlated expression of informative genes.

A lower Allred score for progesterone receptor is strongly associated with a higher recurrence score of 21-gene assay in breast cancer

Among the 77 infiltrating breast carcinomas, we found that progesterone receptor (PR) expression was inversely associated with recurrence score (RS, p < .0001). RS is also significantly associated with tubule formation, mitosis, and luminal B subtype. The equation of RS = 17.489 + 2.071 (tubal formation) + 2.926 (mitosis) -2.408 (PR) -1.061 (HER2) + 7.051 (luminal A) + 29.172 (luminal B) predicts RS with an R² of 0.65. In conclusion, PR negativity, luminal B subtype, tubal formation, and mitosis are strongly correlated with a higher RS.

Prediction of benefit from adjuvant treatment in patients with breast cancer

With the increasingly early diagnosis of breast cancer and the advent of breast tumor subtyping, the need for determining which patients need adjuvant therapy has become more pressing and more complex. While clinical and pathologic features to predict benefit are valuable, the use of molecular techniques to better determine which tumors will benefit from chemotherapy is expected to further improve outcomes, reduce long-term complications, and provide cost-effective care. We will review the primary tools in clinical use: Adjuvant!, Oncotype DX, and MammaPrint as well as intrinsic subtypes and the plans for their further assessment in the clinical trial setting. The expected benefit from these models are that treatment recommendations for women with early-stage breast cancer will become more individualized and thereby appropriate by combining standard clinicopathologic and molecular features. This concept is currently being evaluated in multiple well-designed clinical trials.

Breast cancer assessment tools and optimizing adjuvant therapy

Recommendation of systemic adjuvant therapy and choice of optimal agents for early-stage breast cancer remains a challenge. Adjuvant therapy is indicated on the assumption of residual micrometastatic disease. Adjuvant assessment tools for prognosis and prediction of treatment benefit, including Adjuvant! Online, the St Gallen Consensus, Oncotype DX(®) and MammaPrint(®), aid clinical decision making. However, all of these tools have limitations that must be considered in their judicious application. Clinicopathological based tools are critically dependent on accurate, standardized measurement of parameters. Multigene tools are appealing for their objectivity and reproducibility, particularly regarding analysis of proliferation, but these approaches still overlook the biological heterogeneity within tumors evidenced by distinct cell subpopulations with different genomic patterns and function. The greatest treatment challenge remains for patients assessed as intermediate risk of relapse, a problem not overcome by multigene tools. Remarkable diversity in breast cancer dictates that adjuvant management must be biologically driven. Future identification of predictive biomarkers for specific chemotherapy sensitivity may allow targeted use of available agents, including anthracyclines, taxanes and DNA damaging agents. The presence of drug targets and targetable signaling pathways, rather than molecularly defined subgroups, may ultimately drive treatment decisions.

Clinical application of gene expression profiling in breast cancer

Breast cancer is a heterogeneous disease associated with variable clinical outcomes and response to therapy. Classic clinicopathologic factors associated with outcome include anatomic features associated with prognosis (eg, tumor size, number of positive regional lymph nodes) and biologic features associated with prognosis and/or predictive of response to specific therapies, usually by evaluating protein expression by immunohistochemistry (eg, estrogen and/or progesterone receptors) or amplification of a single gene (eg, HER2/neu). Gene expression profiling evaluating thousands of genes is now feasible, and has facilitated the development of multiparameter assays that may identify breast cancer subtypes associated with distinct clinical outcomes that were not previously recognized, or provide more accurate information about prognosis or response to specific therapies than may be provided by classic clinicopathologic features alone. Several multiparameter gene expression assays are commercially available, and additional assays are being developed that will facilitate more accurate therapeutic individualization.

Benefits of biomarker selection and clinico-pathological covariate inclusion in breast cancer prognostic models

Introduction

Multi-marker molecular assays have impacted management of early stage breast cancer, facilitating adjuvant chemotherapy decisions. We generated prognostic models that incorporate protein-based molecular markers and clinico-pathological variables to improve survival prediction.

Methods

We used a quantitative immunofluorescence method to study protein expression of 14 markers included in the Oncotype DX™ assay on a 638 breast cancer patient cohort with 15-year follow-up. We performed cross-validation analyses to assess performance of multivariate Cox models consisting of these markers and standard clinico-pathological covariates, using an average time-dependent Area Under the Receiver Operating Characteristic curves and compared it to nested Cox models obtained by robust backward selection procedures.

Results

A prognostic index derived from of a multivariate Cox regression model incorporating molecular and clinico-pathological covariates (nodal status, tumor size, nuclear grade, and age) is superior to models based on molecular studies alone or clinico-pathological covariates alone. Performance of this composite model can be further improved using feature selection techniques to prune variables. When stratifying patients by Nottingham Prognostic Index (NPI), the most prognostic markers in high and low NPI groups differed. Similarly, for the node-negative, hormone receptor-positive sub-population, we derived a compact model with three clinico-pathological variables and two protein markers that was superior to the full model.

Conclusions

Prognostic models that include both molecular and clinico-pathological covariates can be more accurate than models based on either set of features alone. Furthermore, feature selection can decrease the number of molecular variables needed to predict outcome, potentially resulting in less expensive assays.

Prediction and prognosis: impact of gene expression profiling in personalized treatment of breast cancer patients

Breast cancer is a complex disease, whose heterogeneity is increasingly recognized. Despite considerable improvement in breast cancer treatment and survival, a significant proportion of patients seems to be over- or undertreated. To date, single clinicopathological parameters show limited success in predicting the likelihood of survival or response to endocrine therapy and chemotherapy. Consequently, new gene expression based prognostic and predictive tests are emerging that promise an improvement in predicting survival and therapy response. Initial evidence has emerged that this leads to allocation of fewer patients into high-risk groups allowing a reduction of chemotherapy treatment. Moreover, pattern-based approaches have also been developed to predict response to endocrine therapy or particular chemotherapy regimens. Irrespective of current pitfalls such as lack of validation and standardization, these pattern-based biomarkers will prove useful for clinical decision making in the near future, especially if more patients get access to this form of personalized medicine.

Genomic index of sensitivity to endocrine therapy for breast cancer

PURPOSE

We hypothesize that measurement of gene expression related to estrogen receptor α (ER; gene name ESR1) within a breast cancer sample represents intrinsic tumoral sensitivity to adjuvant endocrine therapy.

METHODS

A genomic index for sensitivity to endocrine therapy (SET) index was defined from genes coexpressed with ESR1 in 437 microarray profiles from newly diagnosed breast cancer, unrelated to treatment or outcome. The association of SET index and ESR1 levels with distant relapse risk was evaluated from microarrays of ER-positive breast cancer in two cohorts who received 5 years of tamoxifen alone as adjuvant endocrine therapy (n = 225 and 298, respectively), a cohort who received neoadjuvant chemotherapy followed by tamoxifen and/or aromatase inhibition (n = 122), and two cohorts who received no adjuvant systemic therapy (n = 208 and 133, respectively).

RESULTS

The SET index (165 genes) was significantly associated with distant relapse or death risk in both tamoxifen-treated cohorts (hazard ratio [HR] = 0.70, 95% CI, 0.56 to 0.88, P = .002; and HR = 0.76, 95% CI, 0.63 to 0.93, P = .007) and in the chemo-endocrine-treated cohort (HR = 0.19; 95% CI, 0.05 to 0.69, P = .011) independently from pathologic response to chemotherapy, but was not prognostic in two untreated cohorts. No distant relapse or death was observed after tamoxifen alone if node-negative and high SET or after chemo-endocrine therapy if intermediate or high SET.

CONCLUSION

The SET index of ER-related transcription predicted survival benefit from adjuvant endocrine therapy, not inherent prognosis. Prior chemotherapy seemed to enhance the efficacy of adjuvant endocrine therapy related to SET index.

Utility of functional imaging in prediction or assessment of treatment response and prognosis following thermotherapy

The purpose of this review is to examine the roles that functional imaging may play in prediction of treatment response and determination of overall prognosis in patients who are enrolled in thermotherapy trials, either in combination with radiotherapy, chemotherapy or both. Most of the historical work that has been done in this field has focused on magnetic resonance imaging/magnetic resonance spectroscopy (MRI/MRS) methods, so the emphasis will be there, although some discussion of the role that positron emission tomography (PET) might play will also be examined. New optical technologies also hold promise for obtaining low cost, yet valuable physiological data from optically accessible sites. The review is organised by traditional outcome parameters: local response, local control and progression-free or overall survival. Included in the review is a discussion of future directions for this type of translational work.

Is it useful to detect lymphovascular invasion in lymph node-positive patients with primary operable breast cancer?

BACKGROUND

Lymphovascular invasion (LVI) is a widely recognized prognostic factor in lymph node-negative breast cancers. However, there are only limited and controversial data about its prognostic significance in lymph node-positive patients.

METHODS

Among 931 patients operated on and monitored at the authors' institution for an invasive breast carcinoma between 1989 and 1992, all 374 lymph node-positive breast cancers entered the study (median follow-up, 126 months).

RESULTS

LVI was present in 46% of tumors and was associated with age < or = 40 years (P = .02), high histological grade (P = .01), and negative estrogen receptor status (P = .032), but not with tumor size, number of involved lymph nodes, or HER-2/neu status. LVI was an independent prognostic factor for distant metastases (P = .002). Furthermore, in HER-2/neu-negative/hormone receptor-positive (n = 287) tumors, the number of independent prognostic factors (LVI, age, histological grade, number of involved lymph nodes, and tumor size) was associated with a 5-years metastasis-free survival ranging from 100% if no factors (n = 25) to 89% +/- 2% if 1 or 2 factors (n = 186) and 67% +/- 6 if 3, 4, or 5 factors (n = 76) were present (P < .001).

CONCLUSIONS

LVI is an independent prognostic factor in lymph node-positive breast cancer and merits further prospective investigations as a decision tool in the adjuvant chemotherapy setting.

Nomogram for predicting the risk of local recurrence after breast-conserving surgery for ductal carcinoma in situ

PURPOSE

While the mortality associated with ductal carcinoma in situ (DCIS) is minimal, the risk of ipsilateral breast tumor recurrence (IBTR) after breast-conserving surgery (BCS) is relatively high. Radiation therapy (RT) and antiestrogen agents reduce the risk of IBTR and are considered standard treatment options after BCS. However, they have never been proven to improve survival, and in themselves carry rare but serious risks. Individualized estimation of IBTR risk would assist in decision making regarding the various treatment options for women with DCIS.

PATIENTS AND METHODS

From 1991 to 2006, 1,868 consecutive patients treated with BCS for DCIS were identified. A multivariate Cox proportional hazards model was constructed using the 1,681 in whom data were complete. Ten clinical, pathologic, and treatment variables were built into a nomogram estimating probability of IBTR at 5 and 10 years after BCS. The model was validated for discrimination and calibration using bootstrap resampling.

RESULTS

The DCIS nomogram for prediction of 5- and 10-year IBTR probabilities demonstrated good calibration and discrimination, with a concordance index of 0.704 (bootstrap corrected, 0.688) and a concordance probability estimate of 0.686. Factors with the greatest influence on risk of IBTR in the model included adjuvant RT or endocrine therapy, age, margin status, number of excisions, and treatment time period.

CONCLUSION

The DCIS nomogram integrates 10 clinicopathologic variables to provide an individualized risk estimate of IBTR in a woman with DCIS treated with BCS. This tool may assist in individual decision making regarding various treatment options and help avoid over- and undertreatment of noninvasive breast cancer.

Is it prime time for personalized medicine in cancer treatment?

Over the last decade, with rapidly advancing biotechnology, the understanding of cancer has changed. The genomic era has resulted in an explosion of targeted therapies and prognostic and predictive biomarkers. This article aims to illustrate the advances made in the practice of oncology as well as the potential and limitations of personalized medicine in cancer.

Dose-dense chemotherapy for breast cancer: what does the future hold?

Within the last several decades adjuvant polychemotherapy for breast cancer has evolved with the development of anthracyclines and taxanes. Parallel to these developments, granulocyte-colony stimulating factor support has permitted the safe delivery of chemotherapy at shorter (‘dose-dense’) intertreatment intervals, which, as predicted by preclinical models, has further improved survival. Recently, insights into tumor biology have led the development of targeted therapies, such as trastuzumab for HER2-positive disease, and this has now been successfully incorporated into dose-dense therapy. Newer targeted agents may be similarly incorporated into dose-dense regimens to further improve patient outcomes. This article reviews dose-dense therapy and discusses its role as a chemotherapy foundation for additional targeted agents.

Molecular basis for therapy resistance

Chemoresistance remains the main reason for therapeutic failure in breast cancer as well as most other solid tumours. While gene expression profiles related to prognosis have been developed, so far use of such signatures as well as single markers has been of limited value predicting drug resistance. Novel technologies, in particular with regard to high through-put sequencing holds great promises for future identification of the key "driver" mechanisms guiding chemosensitivity versus resistance in breast cancer as well as other malignant conditions.

Phase III multicenter trial of doxorubicin plus cyclophosphamide followed by paclitaxel compared with doxorubicin plus paclitaxel followed by weekly paclitaxel as adjuvant therapy for women with high-risk breast cancer

PURPOSE

This study compared disease-free survival (DFS) obtained with two different regimens of adjuvant therapy in high-risk breast cancer.

METHODS

Women (who had performance status [PS] of 0 to 1) with operable, histologically confirmed, stage I to III adenocarcinoma of the breast were eligible. Patients had undergone primary surgery with no residual tumor. Treatments were as follows: arm 1 was doxorubicin 60 mg/m(2) plus cyclophosphamide 600 mg/m(2) every 3 weeks for four cycles followed by paclitaxel 175 mg/m(2) every 3 weeks for four cycles (ie, AC-P); and arm 2 was doxorubicin 50 mg/m(2) plus paclitaxel 200 mg/m(2) every 3 weeks for four cycles followed by paclitaxel 80 mg/m(2) weekly for 12 weeks.

RESULTS

Overall, 1,830 patients were enrolled and 1,801 were treated: arm 1 (n = 906; AC-->P) and arm 2 (n = 895; AP-WP). Overall, patients had a PS of 0 (88%), had estrogen receptor and progesterone receptor-positive disease (52%), had one to three positive nodes (46%), and were postmenopausal (57%); the median age was 52 years. Currently, 1,640 patients (90%) are alive. The 6-year DFS was 79% to 80% in both groups. Disease relapse was the cause of death for 83 patients in arm 1 and in 66 patients of arm 2. Overall 6-year survival rates were 82% and 87% in arms 1 and 2, respectively. Reasons for patients being taken off study treatment included toxicity (13% in arm 1 v 20% in arm 2), progressive disease or recurrence (7% v 5%), and consent withdrawn (9% v 8%), respectively. The most frequent toxicities were hematologic, including neutropenia and leukopenia followed by neuropathy, myalgia, nausea, fatigue, headache, arthralgia, and vomiting.

CONCLUSION

The results indicate that the AP-WP regimen is an equally effective and tolerable option for the adjuvant treatment of patients with high-risk breast cancer. The substitution of paclitaxel for cyclophosphamide results in comparable effectiveness of the regimen.

Women's experiences with genomic testing for breast cancer recurrence risk

BACKGROUND

Few studies have examined how patients understand and use genomic test results when deciding about treatment. This study examined how women receive and incorporate results of Oncotype DX, a genomic test that offers recurrence risk estimates, into decisions about adjuvant treatment for early stage breast cancer.

METHODS

Participants in the cross-sectional study were 77 women with early stage, estrogen receptor-positive breast cancer with 0 to 3 positive lymph nodes who received Oncotype DX between 2004 and 2009. Mailed surveys, supplemented by medical chart review, assessed how women received and understood recurrence risk information based on the test.

RESULTS

The most common test results were low (50%, 34 of 68) or intermediate (37%, 25 of 68) breast cancer recurrence risk. Most women accurately recalled their recurrence risk based on the test (71%) and felt they understood much of what they were told about it (67%). Approximately 25% of women recalled experiencing test-related distress. Women's perceived recurrence risk was associated with their actual genomic-based recurrence risks, having had a previous cancer diagnosis, and worry about recurrence. Women with high recurrence risk typically had chemotherapy (78%, 7 of 9), whereas only 2 with a low recurrence risk did (7%, 2 of 30).

CONCLUSIONS

This is among the first studies to describe patients' experiences with genomic testing for recurrence risk. Although many women understood discussions about their genomic test results, a third reported not fully understanding these discussions, suggesting a need to aid and improve risk communication and treatment decision making.

Gene-expression-based prognostic assays for breast cancer

Several gene-expression-based reference laboratory tests are now available for prognostication of patients diagnosed with breast cancer. For clinical oncologists, it is important to understand the clinical contexts for which these assays were developed in order to use them properly. This Review is aimed at providing a conceptual and technical overview of the steps involved in the development of gene-expression profiling-based prognostic assays. MammaPrint and Oncotype DX, two widely utilized assays, are compared with respect to differences in the clinical contexts for their development, technologies used, and clinical utilities with the aim of providing a guide to clinical oncologists for utilization of these assays.

Review of the clinical studies using the 21-gene assay

PURPOSE

A major challenge in treating early-stage hormone receptor (HR)(+) breast cancer is selecting women who, after initial surgery, do not require chemotherapy. Better prognostic and predictive tests are needed. The 21-gene assay is the only widely commercially available gene signature that can be performed on formalin-fixed paraffin-embedded tissue.

METHODS

We conducted a review of the literature supporting the prognostic and predictive ability of the 21-gene assay in HR(+) node-negative and node-positive breast cancer patients in chemotherapy-/endocrine-treated and untreated populations. We considered: (a) How accurate is the recurrence score (RS) as a prognostic factor for distant recurrence? (b) How accurate is the RS as a predictive factor for benefit from systemic therapy? (c) How does the RS compare with other prognostic/predictive factors such as tumor size, tumor grade, patient age, and integrated decision aids such as Adjuvant! Online? (d) How do patients and physicians view the 21-gene assay? (e) What are the cost implications of the 21-gene assay?

RESULTS

The 21-gene assay: (a) provided accurate risk information; (b) predicted response to cyclophosphamide, methotrexate, and 5-fluorouracil and to cyclophosphamide, doxorubicin, and 5-fluorouracil chemotherapy; (c) added additional information to traditional biomarkers; (d) was viewed positively by both physicians and patients; and (e) fell within the cost-effectiveness values in North America.

CONCLUSION

This assay may be offered to patients with node-negative HR(+) breast cancer to assist in adjuvant treatment decisions. Data are accumulating to support the use of the 21-gene assay in HR(+) node-positive patients.

New strategies in estrogen receptor-positive breast cancer

Endocrine therapy has led to a significant improvement in outcomes for women with estrogen receptor-positive (ER+) breast cancer. Current questions in the adjuvant setting include the optimal duration of endocrine therapy, and the accurate molecular prediction of endocrine responsiveness using gene array-based assays compared with ER expression itself. In advanced disease, novel selective estrogen receptor antagonists (SERM) have failed to make an impact, although the pure ER antagonist fulvestrant may have a role, albeit optimal dose and sequence remain unclear. Overcoming de novo or acquired endocrine resistance remains critical to enhancing further the benefit of existing endocrine therapies. Recent progress has been made in understanding the molecular biology associated with acquired endocrine resistance, including adaptive "cross-talk" between ER and peptide growth factor receptor pathways such as epidermal growth factor receptor (EGFR)/human epidermal growth factor receptor 2 (HER2). Future strategies that are being evaluated include combining endocrine therapy with inhibitors of growth factor receptors or downstream signaling pathways, to treat or prevent critical resistance pathways that become operative in ER+ tumors. Preclinical experiments have provided great promise for this approach, although clinical data remain mixed. Enriching trial recruitment by molecular profiling of different ER+ subtypes will become increasingly important to maximize additional benefit that new agents may bring to current endocrine therapies for breast cancer.

Prediction of risk of distant recurrence using the 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study

PURPOSE To determine whether the Recurrence Score (RS) provided independent information on risk of distant recurrence (DR) in the tamoxifen and anastrozole arms of the Arimidex, Tamoxifen, Alone or in Combination (ATAC) Trial. PATIENTS AND METHODS RNA was extracted from 1,372 tumor blocks from postmenopausal patients with hormone receptor-positive primary breast cancer in the monotherapy arms of ATAC. Twenty-one genes were assessed by quantitative reverse transcriptase polymerase chain reaction, and the RS was calculated. Cox proportional hazards models assessed the value of adding RS to a model with clinical variables (age, tumor size, grade, and treatment) in node-negative (N0) and node-positive (N+) women. RESULTS Reportable scores were available from 1,231 evaluable patients (N0, n = 872; N+, n = 306; and node status unknown, n = 53); 72, 74, and six DRs occurred in N0, N+, and node status unknown patients, respectively. For both N0 and N+ patients, RS was significantly associated with time to DR in multivariate analyses (P < .001 for N0 and P = .002 for N+). RS also showed significant prognostic value beyond that provided by Adjuvant! Online (P < .001). Nine-year DR rates in low (RS < 18), intermediate (RS = 18 to 30), and high RS (RS > or = 31) groups were 4%, 12%, and 25%, respectively, in N0 patients and 17%, 28%, and 49%, respectively, in N+ patients. The prognostic value of RS was similar in anastrozole- and tamoxifen-treated patients. CONCLUSION This study confirmed the performance of RS in postmenopausal HR+ patients treated with tamoxifen in a large contemporary population and demonstrated that RS is an independent predictor of DR in N0 and N+ hormone receptor-positive patients treated with anastrozole, adding value to estimates with standard clinicopathologic features.

The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade

In the last decade, the development of microarrays and the ability to perform massively parallel gene expression analysis of human tumours were received with great excitement by the scientific community. The promise of microarrays was of apocalyptic dimensions, with some experts envisaging that it would be a matter of a few years for this technology to replace traditional clinicopathological markers in clinical practice and treatment decision-making. The replacement of histopathology by high-tech and more objective approaches to cancer diagnosis, prognostication and prediction was, at that time, a foregone conclusion. Ten years after the initial publications of translational research studies using microarrays, one cannot deny that this technology has changed the way breast cancer is perceived. It has brought the concept of breast cancer heterogeneity to the forefront of cancer research, and the fact that distinct subtypes of breast cancer are completely different diseases that affect the same anatomical site. Furthermore, it has led to the development of prognostic and predictive 'gene signatures', which are yet to be fully incorporated into clinical practice. Importantly, though, the prognostic and predictive power of microarrays has been shown to be complementary to, rather than a replacement for, traditional clinicopathological parameters. Here we endeavour to provide a fair and balanced assessment of what microarray-based gene expression analysis has taught us in the last decade and its contribution to breast cancer classification, prognostication and prediction.

Molecular risk assessment of BIG 1-98 participants by expression profiling using RNA from archival tissue

Background

The purpose of the work reported here is to test reliable molecular profiles using routinely processed formalin-fixed paraffin-embedded (FFPE) tissues from participants of the clinical trial BIG 1-98 with a median follow-up of 60 months.

Methods

RNA from fresh frozen (FF) and FFPE tumor samples of 82 patients were used for quality control, and independent FFPE tissues of 342 postmenopausal participants of BIG 1-98 with ER-positive cancer were analyzed by measuring prospectively selected genes and computing scores representing the functions of the estrogen receptor (eight genes, ER_8), the progesterone receptor (five genes, PGR_5), Her2 (two genes, HER2_2), and proliferation (ten genes, PRO_10) by quantitative reverse transcription PCR (qRT-PCR) on TaqMan Low Density Arrays. Molecular scores were computed for each category and ER_8, PGR_5, HER2_2, and PRO_10 scores were combined into a RISK_25 score.

Results

Pearson correlation coefficients between FF- and FFPE-derived scores were at least 0.94 and high concordance was observed between molecular scores and immunohistochemical data. The HER2_2, PGR_5, PRO_10 and RISK_25 scores were significant predictors of disease free-survival (DFS) in univariate Cox proportional hazard regression. PRO_10 and RISK_25 scores predicted DFS in patients with histological grade II breast cancer and in lymph node positive disease. The PRO_10 and PGR_5 scores were independent predictors of DFS in multivariate Cox regression models incorporating clinical risk indicators; PRO_10 outperformed Ki-67 labeling index in multivariate Cox proportional hazard analyses.

Conclusions

Scores representing the endocrine responsiveness and proliferation status of breast cancers were developed from gene expression analyses based on RNA derived from FFPE tissues. The validation of the molecular scores with tumor samples of participants of the BIG 1-98 trial demonstrates that such scores can serve as independent prognostic factors to estimate disease free survival (DFS) in postmenopausal patients with estrogen receptor positive breast cancer.

Trial Registration

Current Controlled Trials: NCT00004205

Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial

BACKGROUND

The 21-gene recurrence score assay is prognostic for women with node-negative, oestrogen-receptor-positive breast cancer treated with tamoxifen. A low recurrence score predicts little benefit of chemotherapy. For node-positive breast cancer, we investigated whether the recurrence score was prognostic in women treated with tamoxifen alone and whether it identified those who might not benefit from anthracycline-based chemotherapy, despite higher risks of recurrence.

METHODS

The phase 3 trial SWOG-8814 for postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer showed that chemotherapy with cyclophosphamide, doxorubicin, and fluorouracil (CAF) before tamoxifen (CAF-T) added survival benefit to treatment with tamoxifen alone. Optional tumour banking yielded specimens for determination of recurrence score by RT-PCR. In this retrospective analysis, we assessed the effect of recurrence score on disease-free survival by treatment group (tamoxifen vs CAF-T) using Cox regression, adjusting for number of positive nodes.

FINDINGS

There were 367 specimens (40% of the 927 patients in the tamoxifen and CAF-T groups) with sufficient RNA for analysis (tamoxifen, n=148; CAF-T, n=219). The recurrence score was prognostic in the tamoxifen-alone group (p=0.006; hazard ratio [HR] 2.64, 95% CI 1.33-5.27, for a 50-point difference in recurrence score). There was no benefit of CAF in patients with a low recurrence score (score <18; log-rank p=0.97; HR 1.02, 0.54-1.93), but an improvement in disease-free survival for those with a high recurrence score (score > or =31; log-rank p=0.033; HR 0.59, 0.35-1.01), after adjustment for number of positive nodes. The recurrence score by treatment interaction was significant in the first 5 years (p=0.029), with no additional prediction beyond 5 years (p=0.58), although the cumulative benefit remained at 10 years. Results were similar for overall survival and breast-cancer-specific survival.

INTERPRETATION

The recurrence score is prognostic for tamoxifen-treated patients with positive nodes and predicts significant benefit of CAF in tumours with a high recurrence score. A low recurrence score identifies women who might not benefit from anthracycline-based chemotherapy, despite positive nodes.

FUNDING

National Cancer Institute and Genomic Health.

Relationship between Topoisomerase 2A RNA Expression and Recurrence after Adjuvant Chemotherapy for Breast Cancer

PURPOSE: To perform an exploratory analysis of the relationship between gene expression and recurrence in operable hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-normal breast cancer patients treated with adjuvant doxorubicin-containing chemotherapy. EXPERIMENTAL DESIGN: RNA was extracted from archived tumor samples derived from 378 patients with stage I to III HR-positive, HER2-normal breast cancer and analyzed by reverse transcription-PCR for a panel of 374 genes, including the 21-gene recurrence score (RS). Patients were randomized to receive adjuvant doxorubicin plus cyclophosphamide or docetaxel in trial E2197, with no difference in recurrence seen in the treatment arms. All available recurrent cases were selected plus a nonrecurrent cohort. Cox proportional hazard models were used to identify relationships between gene expression and recurrence. RESULTS: TOP2A expression exhibited the strongest association with increased recurrence risk (P = 0.01), and was significantly associated with recurrence (P = 0.008) in a multivariate analysis adjusted for clinicopathologic features. Elevated TOP2A expression above the median was associated with a 2.6-fold increase (95% confidence interval, 1.3-5.2; P = 0.008) in risk of recurrence if the RS was <18, and a 2.0-fold increase (95% confidence interval, 1.2-3.2, P = 0.003) if there was an intermediate RS of 18 to 30. CONCLUSIONS: In patients with HR-positive, HER2-normal breast cancer, a population known to have a low incidence of TOP2A gene alterations thought to be predictive of anthracycline benefit, there is a range of TOP2A RNA expression that is strongly associated with recurrence after adjuvant anthracyclines, which provides information complementary to RS, indicating that it merits further evaluation as a prognostic and predictive marker. (Clin Cancer Res 2009;15(24):7693-700).

Survival analysis of cancer risk reduction strategies for BRCA1/2 mutation carriers

PURPOSE

Women with BRCA1/2 mutations inherit high risks of breast and ovarian cancer; options to reduce cancer mortality include prophylactic surgery or breast screening, but their efficacy has never been empirically compared. We used decision analysis to simulate risk-reducing strategies in BRCA1/2 mutation carriers and to compare resulting survival probability and causes of death.

METHODS

We developed a Monte Carlo model of breast screening with annual mammography plus magnetic resonance imaging (MRI) from ages 25 to 69 years, prophylactic mastectomy (PM) at various ages, and/or prophylactic oophorectomy (PO) at ages 40 or 50 years in 25-year-old BRCA1/2 mutation carriers.

RESULTS

With no intervention, survival probability by age 70 is 53% for BRCA1 and 71% for BRCA2 mutation carriers. The most effective single intervention for BRCA1 mutation carriers is PO at age 40, yielding a 15% absolute survival gain; for BRCA2 mutation carriers, the most effective single intervention is PM, yielding a 7% survival gain if performed at age 40 years. The combination of PM and PO at age 40 improves survival more than any single intervention, yielding 24% survival gain for BRCA1 and 11% for BRCA2 mutation carriers. PM at age 25 instead of age 40 offers minimal incremental benefit (1% to 2%); substituting screening for PM yields a similarly minimal decrement in survival (2% to 3%).

CONCLUSION

Although PM at age 25 plus PO at age 40 years maximizes survival probability, substituting mammography plus MRI screening for PM seems to offer comparable survival. These results may guide women with BRCA1/2 mutations in their choices between prophylactic surgery and breast screening.

Genomic predictors of outcome and treatment response in breast cancer

Despite advances in breast cancer treatment and outcome over the last two decades, women continue to relapse and die of advanced disease. Historically, estrogen and progesterone receptor expression, HER2 overexpression and clinico-pathologic parameters have guided therapeutic decision making. However, there are limits to the risk estimation provided by these parameters, leading to potential overtreatment of low-risk disease and undertreatment of poor-risk disease. Genomic technologies now provide the opportunity to refine our therapeutic approach by individualizing treatment to patients' individual tumor profiles. Gene profiles or signatures are groupings of genes that are differentially expressed between tumors, reflecting differences in biologic behavior. Prognostic gene signatures stratify breast cancer patients by tumor natural history, regardless of the treatment employed. Currently, there are three commercially available prognostic gene signatures: Oncotype DX (Genomic Health, Inc.), MammaPrint (Agendia BV), and the HOXB13/IL17BR (H/I) ratio; (Theros H/ISM; bioTheranostics). Others under development include the Intrinsic Gene Set, the Rotterdam Signature, the Wound Response Indicator, and the Invasive Gene Signature. Predicative signatures classify patients based on responsiveness to specific therapies. Of the prognostic signatures, Oncotype DX has been shown to have predictive value for the incremental benefit of chemotherapy when added to a hormonal therapy regimen. Additional genetic profiles under development predict response to specific hormonal therapies, anthracyclines, and taxanes. Gene signatures have the potential to transform breast cancer treatment as it becomes tailored to each patient's tumor expression profile and significantly improve the outcomes of this disease.

Verification of a prolonged untreated natural history of breast cancer by the multigene assay

Individualization of therapy for breast cancer patients has progressed significantly over the last 5 years. A 54-year-old female went over 2 years after her diagnosis of breast cancer with no treatment. The pathologic size, however, indicated that the tumor may not have progressed from diagnosis to operation. Due to the apparent lack of progression over 2 years without treatment, a multigene assay was ordered. The recurrence score was 15, indicating a less than 10% risk of distant recurrence at 10 years. The recurrence score also falls into the "low risk" category. The prolonged natural history of this breast cancer patient suggested an indolent cancer. The "low risk" recurrence score confirmed this history and indicated that adjuvant chemotherapy is probably not beneficial to this patient.

Novel molecular prognostic markers in breast cancer

BACKGROUND

Advances in the treatment of breast cancer have led to a reduction in breast-cancer-related mortality. However, these therapies are known to be associated with toxicities. Thus there is a crucial need to accurately define the populations of women with an excellent prognosis who may safely avoid the risks of systemic therapy. Recent developments utilizing novel technologies that incorporate our growing understanding of the biology and pathophysiology of breast cancer strive to better identify these patients.

OBJECTIVE

To provide a review of newer prognostic markers with a focus on the 21-gene recurrence score (Oncotype DX(™)), 70-gene prognosis profile (Mammaprint(®)), and Adjuvant! Online.

CONCLUSION

These techniques differ in their execution and application and have been demonstrated to provide further data on risk stratification as compared with conventional breast-cancer-risk factors.

Comparison of prognostic gene profiles using qRT-PCR in paraffin samples: a retrospective study in patients with early breast cancer

Introduction

Gene profiling may improve prognostic accuracy in patients with early breast cancer, but this technology is not widely available. We used commercial assays for qRT-PCR to assess the performance of the gene profiles included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Ratio.

Methods

153 patients with early breast cancer and a minimum follow-up of 5 years were included. All tumours were positive for hormonal receptors and 38% had positive lymph nodes; 64% of patients received adjuvant chemotherapy. RNA was extracted from formalin-fixed paraffin-embedded (FFPE) specimens using a specific kit. qRT-PCR amplifications were performed with TaqMan Gene Expression Assays products. We applied the three gene-expression-based models to our patient cohort to compare the predictions derived from these gene sets.

Results

After a median follow-up of 91 months, 22% of patients relapsed. The distant metastasis-free survival (DMFS) at 5 years was calculated for each profile. For the 70-Gene Signature, DMFS was 95% -good prognosis- versus 66% -poor prognosis. In the case of the Recurrence Score, DMFS was 98%, 81% and 69% for low, intermediate and high-risk groups, respectively. Finally, for the Two-Gene Ratio, DMFS was 86% versus 70%. The 70-Gene Signature and the Recurrence Score were highly informative in identifying patients with distant metastasis, even in multivariate analysis.

Conclusion

Commercially available assays for qRT-PCR can be used to assess the prognostic utility of previously published gene expression profiles in FFPE material from patients with early breast cancer. Our results, with the use of a different platform and with different material, confirm the robustness of the 70-Gene Signature and represent an independent test for the Recurrence Score, using different primer/probe sets.

Recent advances in systemic therapy: new diagnostics and biological predictors of outcome in early breast cancer

The key to optimising our approach in early breast cancer is to individualise care. Each patient has a tumour with innate features that dictate their chance of relapse and their responsiveness to treatment. Often patients with similar clinical and pathological tumours will have markedly different outcomes and responses to adjuvant intervention. These differences are encoded in the tumour genetic profile. Effective biomarkers may replace or complement traditional clinical and histopathological markers in assessing tumour behaviour and risk. Development of high-throughput genomic technologies is enabling the study of gene expression profiles of tumours. Genomic fingerprints may refine prediction of the course of disease and response to adjuvant interventions. This review will focus on the role of multiparameter gene expression analyses in early breast cancer, with regards to prognosis and prediction. The prognostic role of genomic signatures, particularly the Mammaprint and Rotterdam signatures, is evolving. With regard to prediction of outcome, the Oncotype Dx multigene assay is in clinical use in tamoxifen treated patients. Extensive research continues on predictive gene identification for specific chemotherapeutic agents, particularly the anthracyclines, taxanes and alkylating agents.

Weighted analyses for cohort sampling designs

Weighted analysis methods are considered for cohort sampling designs that allow subsampling of both cases and non-cases, but with cases generally sampled more intensively. The methods fit into the general framework for the analysis of survey sampling designs considered by Lin (Biometrika 87:37-47, 2000). Details are given for applying the general methodology in this setting. In addition to considering proportional hazards regression, methods for evaluating the representativeness of the sample and for estimating event-free probabilities are given. In a small simulation study, the one-sample cumulative hazard estimator and its variance estimator were found to be nearly unbiased, but the true coverage probabilities of confidence intervals computed from these sometimes deviated significantly from the nominal levels. Methods for cross-validation and for bootstrap resampling, which take into account the dependencies in the sample, are also considered.

Microarray-based Gene Expression Profiling as a Clinical Tool for Breast Cancer Management: Are We There Yet?

Breast cancer is a heterogeneous disease, encompassing several histological types and clinical behaviors. Current histopathological classification systems are based on descriptive entities with prognostic significance. Few prognostic and predictive markers beyond those offered by histopathological analysis are available. High-throughput molecular technologies are reshaping our understanding of breast cancer, of which microarray-based gene expression has received most attention. This method has been used to derive a molecular taxonomy for breast cancer, which has provided interesting insights into the biology of the disease. Class prediction studies have generated a multitude of prognostic/predictive signatures, which herald the promise for an improvement in treatment decision making. However, most of the signatures developed to date seem to have discriminatory power almost restricted to estrogen receptor—positive disease. This review addresses the contribution of gene expression profiling to our understanding of breast cancer and its clinical management.

A 38-gene expression signature to predict metastasis risk in node-positive breast cancer after systemic adjuvant chemotherapy: a genomic substudy of PACS01 clinical trial

Currently, no prognostic gene-expression signature (GES) established from node-positive breast cancer cohorts, able to predict evolution after systemic adjuvant chemotherapy, exists. Gene-expression profiles of 252 node-positive breast cancer patients (median follow-up: 7.7 years), mostly included in a randomized clinical trial (PACS01), receiving systemic adjuvant regimen, were determined by means of cDNA custom array. In the training cohort, we established a GES composed of 38 genes (38-GES) for the purpose of predicting metastasis-free survival. The 38-GES yielded unadjusted hazard ratio (HR) of 4.86 (95% confidence interval = 2.76-8.56). Even when adjusted with the best two clinicopathological prognostic indexes: Nottingham prognostic index (NPI) and Adjuvant!, 38-GES HRs were 3.30 (1.81-5.99) and 3.40 (1.85-6.24), respectively. Furthermore, 38-GES improved NPI and Adjuvant! classification. In particular, NPI intermediate-risk patients were divided into 2/3 close to low-risk group and 1/3 close to high-risk group (HR = 6.97 [2.51-19.36]). Similarly, Adjuvant! intermediate-risk patients were divided into 2/3 close to low-risk group and 1/3 close to high-risk group (HR = 4.34 [1.64-11.48]). The 38-GES was validated on gene-expression datasets from three external node-positive breast cancer subcohorts (n = 224) generated from different microarray platforms, with HR = 2.95 (1.74-5.01). Moreover, 38-GES showed prognostic performance in supplementary cohorts with different lymph-node status and endpoints (1,040 new patients). The 38-GES represents a robust tool able to type systemic adjuvant treated node-positive patients at high risk of metastatic relapse, and is especially powerful to refine NPI and Adjuvant! classification for those patients.